Goals — Our goals are to understand the acquisition, retention and representation of information in the cerebral cortex that underlie behavioral memory. In contrast to traditional assumptions, primary sensory cortex is a substrate of memory rather than merely a sensory analyzer. Because primary sensory fields contain systematic “maps” of sensory parameters, they provide an opportune target for the study of representations. We focus on the primary auditory cortex (termed “A1”) due to the wealth of learning/memory studies that use acoustic stimuli. A1 contains a representational “tonotopic map” of acoustic frequency similar to the organization of a piano keyboard. Unlike a keyboard, A1 frequency representation is not fixed but is plastic, becoming “retuned” when a tone gains (or loses) behavioral importance during learning. We use a three-level attack.

Higher (Cortical) Associative Representational Plasticity (HARP) — Our lab pioneered the combined study of sensory physiology and learning/memory by findings that associative learning shifts cellular receptive fields (frequency tuning) to the frequency of a signal tone. Across the tonotopic map, the signal tone gains representational cortical area. Thus, HARP is revealed to be a systematic modification of cortical representations along a dimension, even during learning with a single stimuli. Representational plasticity develops in a wide variety of tasks, in all species tested (including humans) and has all the characteristics of major forms of memory: associativity, specificity, rapid acquisition, indefinite long-term retention (months) and consolidation (continued development over hours & days). Learning strategy (“how” a task is solved) can determine the formation of representational plasticity and in fact can trump the amount of training or the level of motivation.

Nucleus Basalis Induction of HARP and Implanted Behavioral Memory — A laboratory model hypothesized that the release of acetylcholine (ACh) in the cortex from activation of the nucleus basalis (NB) promotes the long-term storage of HARP as a substrate of memory. Indeed, pairing a tone with stimulation of the NB was found to induce muscarinic-dependent RF plasticity that has all the major attributes of associative memory. Remarkably, muscarinic-dependent specific behaviorally verified memories can be “implanted” in the rat by pairing a tone with NB stimulation. Furthermore, the degree of specificity of implanted memory can be determined by the amount of ACh released in the auditory cortex. Implanted memory also has the cardinal characteristics of “natural” memory. Also, activation of the basolateral amygdala (BLA), an established modulator of memory strength, can induce signal-specific tuning shifts in A1, perhaps via the NB, suggesting memory strength is linked to areal expansion.

Neural Memory Codes — We hypothesized that there are Memory Codes analogous to Sensory Codes for stimulus parameters. Studies of instrumental auditory tasks combined with mapping of A1 have found strong evidence for Memory Codes. For example, there appears to be a code for the acquired importance of stimuli —

“The importance of the memory of a stimulus is a direct increasing function of the number of neurons that optimally process or become tuned to that stimulus.”

As memories of greater behavioral importance should be stronger, we determined the relationship between memory strength (via resistance to extinction) and representational area. We found evidence for another Memory Code —

“The strength of memory is proportional to the amount of expanded representational area for a signal: the greater the area, the stronger the memory.”

Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA 92697-3800